assessing the impact of china’s wto accession on investment
TRANSCRIPT
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Assessing the Impact of China’s WTO Accession on Investment
Terrie L. Walmsley, Thomas W. Hertel and Elena Ianchovichina*
Abstract
During the early 1990s, foreign direct investment (FDI) in China boomed, subsequently claiming a large share of all Foreign Direct Investment in developing countries. However, the rate of growth in FDI slowed in the later 1990’s, as investors’ high expectations failed to fully materialize. With China’s accession to the WTO at long last a reality, FDI growth has once again picked up. This paper formally explores the linkage between WTO accession and investment in China over the next two decades. The effects of a number of features of China’s accession are examined, including: the removal of tariffs and quotas, the potential for improved productivity in the automobile sector due to production rationalization, and finally, the liberalization of rules governing direct trade and foreign investment in the service sectors.
We find that investment and capital stocks increase substantially as a result of China’s accession. Moreover, accession doubles the extent of foreign ownership of Chinese assets relative to the no-accession baseline by 2020. Central to this increase in foreign ownership is the expected catch-up in the productivity of the services sectors driven by the opening up of these sectors to foreign investment. The resulting impact on GDP is also large -- 22.5% higher in 2020 as a result of WTO accession. The static welfare gains (16% by 2020) are dampened due to the fact that a substantial share of the additional investment comes from overseas. These estimates are far larger than those predicted by earlier studies, which ignored the reforms affecting the services sectors of China, and which also abstracted from capital accumulation and international capital mobility. Given its critical importance to our analysis, future research should be directed towards narrowing the uncertainty associated with the impact of accession on productivity in the services sectors.
*Walmsley is an Assistant Professor at the Center for Global Trade Analysis, Purdue University, 403 West State Street, West Lafayette, IN 47906, USA, Email: [email protected]. Hertel is a professor at the Center for Global Trade Analysis, Purdue University, USA and Ianchovichina is an economist at the World Bank, 1818 H Street, N.W., Washington D.C 20433, USA.
We would like to thank the reviewers of this paper for their useful comments and suggestions. Also we thank the participants of the Fourth Annual Conference on Global Economic Analysis, Purdue University, USA, June and the ESRC Development Economics Study Group Annual Conference, April 2002 for their comments.
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1. Introduction
Over the last two decades, China has undertaken significant reforms to restructure and
open up its economy to foreign trade. These reforms have helped to spur a period of rapid
growth, with growth in real per capita GDP averaging 6.04 percent over the period 1978-95
(Maddison, 1998). However, reforms to the legislative framework governing foreign investment
in China have proceeded more slowly. Entry in certain sectors, as well as the share of foreign
ownership, is significantly limited and joint ventures typically remain the best option for foreign
investors. In an effort to boost foreign investment, the Chinese government began offering a
number of special incentives in the early 1990’s, including duty drawbacks on imported
intermediate inputs and capital goods used for the production of exports, exemptions and
reductions in the rate of income taxes paid on profits,1 and preferential tax rates for foreign
enterprises which re-invest their profits (China Council, 2000). These incentives paid off, with
foreign investment increasing sharply in 1992-93 (Figure 1). Indeed, by 1994 China accounted
for approximately 20 percent of all Foreign Direct Investment (FDI) in developing countries
(Garbaccio, 1995).
However, by 1996 the rate of growth in FDI had begun to slow (Figure 1). A survey of
the Chinese economy by The Economist (2000) explored some of the reasons behind the FDI
slowdown in China. In many cases investors’ high hopes for this market were slow to
materialize, with the absence of a rules-based economy making it difficult for outsiders to
operate effectively in China. Informal relationships and corruption still hinder many business
transactions by foreigners. In addition, inefficient state enterprises still dominate many key
sectors of the economy. China’s push for accession to the World Trade Organization (WTO) was
partly an attempt to remedy some of these more fundamental problems, thereby promoting
foreign investment. Indeed, the recent upturn in FDI provides some evidence that investors have
responded positively to China’s accession. It is this linkage between WTO accession and foreign
investment that provides the focal point for our paper.
1 Incentives are numerous and depend on the sector and/or the region within China where the investment is undertaken as well as the purpose of the production activity (e.g., export sales). The duration of incentives also varies, and may be for a period of up to five years (China Council, 2000).
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China’s bid to rejoin the GATT began in 1986, and culminated in the recent Doha
meetings of the WTO, when membership was finally approved by that body. The final accession
agreement reflects the importance, to the US and European negotiators, of increasing access for
foreign investors – particularly in the services sectors. In the words of Aaditya Mattoo of the
World Bank: “China’s GATS commitments represent the most radical services reform program
negotiated in the WTO. China has promised to eliminate over the next few years most
restrictions on foreign entry and ownership, as well as most forms of discrimination against
foreign firms” (Mattoo, 2001). Clearly the stage is set for increases in foreign investment.
Domestic investment is also expected to rise as a result of WTO accession. In the nineties
FDI inflows surged because domestic firms were uncompetitive, domestic savings were
inefficiently allocated and laws put domestic companies at a disadvantage relative to foreign
companies (Huang, 2002).2 Tax advantages for export processing has benefited mainly foreign-
owned companies, while domestic content requirements restricted the use of imported
intermediate inputs by companies selling locally and were a particular problem for the domestic
automobile industry. In preparation for WTO accession China reformed its export processing
system and extended tax benefits to all companies producing exports, not only the foreign-owned
ones. Commitments as part of WTO accession have led to the removal of the local content
requirement, and reforms will ensure fair treatment for both domestic and foreign companies (no
discrimination) and more efficient use of domestic savings. Therefore, it is expected that China’s
WTO accession will have a positive impact on domestic investment.
The accession agreement also provides for the reduction of tariffs, the implementation of
tariff bindings, and elimination of quantitative restrictions. These have been the focus of the vast
majority of previous papers on China’s WTO accession.
In this paper we explore the implications of China’s accession to the WTO for investment
in China using a revised version of the dynamic GTAP model (GTAP-Dyn) (Ianchovichina and
McDougall, 2001), which explicitly accounts for duty drawbacks by modeling the export
processing sectors separately. This analysis goes beyond the impact of the associated tariff cuts.
It examines the impact of the liberalization of rules governing direct trade in services, the
2 The result was an increase in FDI even in industries in which Chinese firms have been strong in the past such as textiles, herbs, and others.
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elimination of quantitative restrictions on textiles and apparel exports to North America and the
European Union, and the impact of prospective productivity gains in the automobiles and
services sectors.
Our basic macro-economic results confirm the findings of the earlier studies
(Ianchovichina and Martin, 2001, 2003; Wang, 2001) with China expected to gain most from
accession. The new insight from our paper relates to the implications for investment and
ownership of productive assets. We find that accession significantly boosts investment, doubling
the extent of foreign ownership of Chinese assets relative to the no-accession baseline. Central to
this increase in foreign ownership is the expected boost in productivity of the services sectors
owing to the liberalization of rules governing foreign investment in these sectors.
The next section of this paper reviews the literature examining China’s accession to the
WTO. Section 3 introduces the analytical framework employed to understand the economy-wide
implications of China’s WTO accession, and specifically, the link between accession and
investment. Section 4 discusses the details underlying the design of the accession scenario.
Section 5 examines the results of this scenario, comparing them to the baseline. Finally section 6
summarizes the findings and offers concluding remarks.
2. Literature review
China’s accession to the WTO has generated a large amount of interest and extensive
research has already been undertaken on this topic. Most of this work has focused on the trade
implications of accession – largely abstracting from the likely impact on investment. Anderson et
al. (2000) used the GTAP model to determine some early estimates of the effects of China’s
accession. Ianchovichina and Martin (2001, 2003) updated these estimates by taking into account
duty drawbacks in China.3 Wang (1997a, 1997b, 2001, 2002) has also undertaken a number of
studies examining the effects of China’s WTO accession using the GTAP Data Base. In general,
the results show that world trade increases substantially as a result of China’s accession. The
main winner from China’s accession is China itself. North America and many of the other
developed nations also gain as a result of increased exports, particularly of agricultural products
(Wang, 1997a). The removal of quotas for China’s apparel and textile exports under the ATC
3 Lejour (2000) also examined the effect of duty drawbacks on China’s accession using the GTAP model.
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agreement appears to be a significant contributor to the benefits accruing to North America.
These results are consistent with the findings by other authors (Hertel et al., 1996; Harrison,
Rutherford and Tarr, 1996; Walmsley and Hertel, 2001; Yang, 1996).
Analysis of the impact of China’s WTO accession on investment has been much more
limited. McKibbin and Tang (2000) – henceforth MT – offered an early assessment of this issue.
They used the G-cubed model to examine the effect of three possible developments in China: a)
the liberalization of trade; b) the liberalization of financial markets; and c) the possibility that
financial liberalization might result in a financial crisis within China. MT found that financial
liberalization could result in significant gains, particularly for China itself. They did caution,
however, that many of the problems affecting the Asian economies at the time of the Asian
crisis, such as a fragile banking system, were also features of the Chinese economy, and
therefore argued that financial liberalization would be much riskier than liberalization of trade.
However, there are a number of limitations to the MT analysis. Firstly, they used a very old data
base (1991), which reflects a very different Chinese economy than that which is poised to join
the WTO. A second limitation is that their analysis was not based on China’s actual offer to the
WTO. Instead their accession scenario was highly stylized, representing full removal of
protection in China from their 1991 base. Finally, MT did not reflect the system of preferences
for export-enterprises in China. Of particular importance is the fact that in 2000 60% of China’s
imports entered the country duty-free due to the current system of duty-exemptions for export
processing firms; implying that the gains from trade liberalization will be smaller than the
estimates obtained without taking into account duty exemptions.
Ianchovichina (2003) found that the failure to account for duty drawbacks could lead to a
substantial overstatement of the impact of WTO accession on China’s light manufacturing
industry. For example, she showed that failure to account for China’s duty exemptions in
analyzing WTO accession resulted in overstating the increase in China’s trade flows by 40
percent and exports of selected sectors by 90 percent. This limitation is even more severe when
one considers the fact that the duty exemptions have been extended to investment goods
imported by joint ventures and foreign-owned companies.
Walmsley and Hertel (2001) (WH) offer a more recent assessment of China’s WTO
accession. While their paper focuses on the uncertainty in the timing of abolition of textile and
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apparel restrictions on China’s exports, they also report findings related to changes in foreign
investment resulting from China’s WTO accession. The WH analysis shares several important
features with the present paper. However, they, too, fail to account for the duty drawback regime
currently in place in China. In addition, WH ignore the problem of revenue replacement. Another
significant limitation of the WH paper has to do with the construction of the baseline scenario in
which the authors show foreign investment declining after 1997. This does not square with what
has been observed since 1999. Moreover, WH focus only on the issue of trade liberalization,
while this paper extends the analysis to encompass liberalization of trade and investment in
services.
We address many of the shortcomings of the WH paper and focus specifically on the
liberalization and productivity gains in the services sector. GTAP-Dyn (Ianchovichina and
McDougall, 2001), used in this paper, places international capital mobility at the forefront,
thereby providing a useful vehicle for exploring the impact of China’s WTO accession on
investment and economic growth in China. We also deal directly with the problem of duty
drawbacks by modeling the export processing sectors separately. Furthermore, while tariff
revenue has receded somewhat from its previously prominent position in the overall revenue
picture for China (tariffs comprised only 6% of total revenue in 1998 versus 14% in 1990), the
fiscal implications of accession remain an important issue. Therefore, we assume that the
Chinese government will replace lost tariff revenue with increased consumption taxes. This
seems quite reasonable, as it reflects a continuation of the trend over the past decade in which
consumption taxes rose from 18% to 79% of total revenue.
The accession agreement used in the paper is based on the August 1999 offer agreed
between China and the United States and is obtained from Martin et al. (2000).4 The agreement
involves the gradual reduction of China’s tariffs, which this paper assumes will commence in
2002, and will be completed 5 years later, by the beginning of 2007. Taiwan’s (China) accession,
which immediately followed on the heels of China’s accession, is also included in the analysis.
4 In most studies on China’s WTO accession, including Ianchovichina and Martin (2001) and Wang (2001), the bilateral agreement between the U.S. and China served as the basis for determining the extent of liberalization due to WTO accession. The agreement cannot be represented as a move to free trade or a simple proportional cut in protection as many studies have tried to do (see Gilbert and Wahl (2001) for a survey). More recently, Ianchovichina and Martin (2003) used the final multilateral commitments, which became publicly available after the Doha meeting. Their results confirm that the U.S.-China bilateral agreement indeed serves as a good basis for assessing the extent of liberalization in China as part of WTO accession.
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In addition to reducing tariffs on goods, we examine the liberalization of rules governing direct
trade in services Estimates of tariff equivalents in the services sector for both China and Taiwan
(China) were obtained from Francois and Spinanger (2002). These are reduced to examine the
potential effect of services liberalization on foreign investment in China.
Accession to the WTO is also expected to produce significant benefits to China through
additional productivity growth due to consolidation of the automobile industry and the opening
up of the service sectors to foreign investment. Francois and Spinanger (2002), estimate that
productivity in China’s automobile sector will increase by 20% as a result of accession. This is
comparable in magnitude to the estimates of Mai, Horridge and Perkins (2003) who predict a
productivity increase of 1.8% per year over 10 years for strategic manufacturing industries,
including autos and parts. Productivity gains are also expected in the services sectors. Mai et al.
(2003) estimate an increase in productivity of 2.7% per year over 10 years in the services sectors
as reforms take place under WTO accession. In this paper we adopt the Francois and Spinanger
(2002) estimates for automobile production, and we scale down the estimates of Mai et al. (2003)
for services. Specifically we assume productivity improvements in services which climb
gradually, reaching a peak of 1% per year in 2007, thereafter declining to zero. In an appendix,
we also examine the case where productivity reaches a peak of 2.7%, the annual growth rate
estimated by Mai et al. (2003).
Finally, special attention is given in the baseline to tracking the growth rate of foreign
ownership over the period 1995-2002 and reflecting the fact that the removal of restrictions on
foreign ownership and trade reform in China in anticipation of WTO accession has already had a
significant effect on the share of foreign investment. We assume that the continued removal of
restrictions on foreign ownership, as part of China’s accession, will continue to attract foreign
investment, although at a declining rate over the period 2002-2007.
2. The Model
In order to analyze the impact of China’s WTO accession on foreign investment, we
extend GTAP-Dyn (Ianchovichina and McDougall, 2001) to take into account duty exemptions
on imported inputs and capital goods used in the production of China’s exports.5 GTAP-Dyn is a
5 We incorporate duty drawbacks into the model following the method outlined in Ianchovichina (2003).
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recursive dynamic extension of the GTAP model (Hertel, 1997; www.gtap.org), which is a
multi-region applied general equilibrium model. The dynamic model preserves all the features of
the GTAP model, while enhancing the investment theory to incorporate capital accumulation,
and international capital mobility and ownership. We apply the model to version 4 of the GTAP
Data Base6 (McDougall et al., 1998), aggregated into 11-regions and 13-sectors (Table 1). The
GTAP Data Base is supplemented with foreign income data from the IMF Balance of Payments
statistics in order to track international capital mobility and foreign wealth.
Given the focus of this paper on investment, we dedicate the remainder of this section to
a brief discussion of the investment theory in the model and the determination of foreign
ownership.
2.1 Investment Theory of the Dynamic GTAP Model
The investment theory in GTAP-Dyn (Ianchovichina and McDougall, 2001) allows us to
link economic activity over time while keeping track of endogenous regional capital stocks and
financial wealth, international investment and income flows. Investment funds are used for the
purchase of physical investment goods, which are then added to the existing stock of physical
capital (Equation 5, Box 1).
The theory offers a disequilibrium approach for allocating investment across regions.
Investors respond to expected rates of return and act so as to eliminate errors in their
expectations gradually over time. In the process of adjustment, investors gradually eliminate any
differences in the rates of return across regions that might exist in the short run by reallocating
capital from regions with lower rates of return to regions with higher rates of return. This leads to
equalization of rates of return across regions only in the long run.7
The determination of investment in the model may be illustrated with the help of Figure
2. The expected rate of return schedule depicts the relationship between the expected rate of
return (RE) and capital stock (K), while the actual rate of return schedule shows the relationship
6 Results are similar when the model is applied to the more recent version 5 of the GTAP Data Base (see Ianchovichina and Walmsley, 2003). 7 The disequilibrium approach is necessary to reconcile the theory of investment with observed reality. In many cases actual investment, as reported in the national statistics, does not correspond to that predicted by theory. For example, observed rates of return may be very low while observed investment is high. Such discrepancies can be rectified in one of two ways – either the data can be altered so that theory and data are consistent, or alternatively, the theory can be modified to more accurately reflect empirical reality. In GTAP-Dyn the latter method was used.
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between the actual rate of return (RA) and capital stock (K). These curves are downward sloping
reflecting the belief that, as capital stocks increase, rates of return will fall, ceteris paribus. The
difference between these two schedules is a result of errors in expectations (i.e. the difference
between observed data and the postulated theory). In any given year, there is a temporary
equilibrium global rate of return, RT that ensures that global savings equal investment.
Investment in a particular year is determined by three mechanisms. The first one, which
forms the second part of equation 1 (Box 1), is the desire to eliminate errors in expectations The
expected rate of return falls by a portion (determined by µ ) of the error in expectations
(log(RA/RE)) during the period (dt). Over time as the expected and actual rates of return converge,
this error will be eliminated. In Figure 2 this involves the movement of the expected rate of
return schedule towards the actual rate of return schedule (arrow 1 in Figure 2).
The second one, incorporated into the model via equation (2) (Box 1), is the gradual
equalization across regions of rates of return. This requires the movement of the expected rate of
return in all regions towards the temporary equilibrium (RT), common to all regions (arrow 2 in
Figure 2). Differences between the expected (RE) and target (RT) rates of return determine the
expected rate of growth in the expected rate of return ( EΓ ). These differences are gradually
eliminated at a rate determined by Λ .
The third mechanism is the equalization of all three rates of return. In the long run the
target and expected rates of return will have converged, leading to an expected rate of growth in
the rate of return of zero (equation 2, Box 1). Errors will also have been eliminated (RA/RE equals
1) and there will be no tendency for the expected rate of return to change ( E
^
R = 0). For this to
occur the growth rate of capital must equal the normal growth rate of capital (first part of
Equation 1, Box 1) and investment and capital must be changing at the same rate (Equation 3,
Box 1)8. Otherwise, rates of return may overshoot the target rate of return. Only when all these
conditions are satisfied will a permanent long-run convergence of rates of return occur.
8 In addition there should be no tendency for the normal growth rate of capital to change (ω= 0, Equation 4 in Box 1). Since the normal growth rate is that rate of growth consistent with no changes in the rate of return, changes in the normal growth rate may arise if the current normal growth rate does appear to lead to changes in the rate of return.
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Box 1: Investment theory of GTAP-Dyn.
1. dtRRdtK AEE )/log()(R^^
µφ −Ω−−=
2.
−Λ=Γ ETE RR
^^
3. Ω+
−=Γ dKI
K
IE φφ
^^
4.
Ω−+Π= dt
RK
A
φω
^^
5. IdtK =^
where: ER is the expected rate of return
AR is the actual rate of return
TR is the target rate of return
K is the quantity of capital stocks
I is Investment
Ω is the normal growth rate of capital – that rate of growth consistent with no change in rates of return dt is change in years
)/log( AE RR is a measure of the errors in expectations
φ is the elasticity of the rate of return with respect to capital stocks
µ is the rate at which errors in expectations are eliminated
EΓ is expected rate of growth in the expected rate of return
Λ is the rate at which differences in the expected and actual rate of return are eliminated ω is the change in the normal growth rate of capital
^ the hat represents proportionate change.
Note: All variables except TR are indexed by region.
2.2 Foreign Ownership
With the incorporation of capital accumulation, it becomes necessary to take account of
foreign capital ownership. With regard to foreign investment, the theory respects the empirical
regularity that regions tend to invest primarily in assets located in their domestic economy, with
a smaller portion of investment coming from abroad. In GTAP-Dyn, financial assets represent
claims on earnings from regional physical capital, owned by domestic households, as well as by
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foreign households (via a global trust).9 In the absence of policy reforms the share of each
regional household’s wealth in domestic and foreign firms and the share of each region’s capital
stocks owned by domestic and foreign residents are held as close as possible to their initial
values, subject to adding-up constraints. The proviso “subject to the adding-up constraints”,
means that these shares are likely to change, however the change is minimized. For example, if
national saving rises faster than national investment then the share of investment funded through
domestic saving is likely to rise.
Explicit modeling of the ownership of national investment in China allows us to track the
accumulation of wealth by foreigners, thereby ascertaining how China’s accession to the WTO
might affect foreign investment and ownership in China. Moreover, by tracking foreign and
domestic ownership, the income accruing from the ownership of these foreign and domestic
assets can then be appropriately incorporated into regional income, and hence into the calculation
of welfare, both for China and for the rest of the world.
3. Modeling China’s Accession to the WTO
The effects of China’s accession are examined over the period 1995 to 2020. This time
frame is divided into a number of unequal intervals to provide the highest resolution over the
accession period. These intervals are as follows: 1995-2000,10 2001, 2002, 2003, 2004, 2005,
2006, 2007, 2008, 2009, 2010, 2010-2015, 2015-2020.
Two simulations are undertaken representing the baseline (without China’s accession)
and the policy scenario (with China’s accession). The baseline scenario provides a picture of
what we expect the world economy to look like without China’s accession to the WTO11 and is
based on Walmsley, Dimaranan and McDougall (2001). The policy simulation examines the
effect of China’s accession on both domestic and foreign investment. We assume that accession
commences in 2002 and that it takes 5 years to implement the agreement; hence accession is
9 The global trust collects all the regional saving allocated to foreign investment, and then allocates it across regions to investment. It is a fictitious agent invented to simplify data requirements for the global model. Without the global trust, a region’s saving would need to be allocated bilaterally (nxn data values, where n equals the number of regions). One of the disadvantages of the global trust method however, is that a small part of the foreign investment undertaken by a region may flow back into the region via the global trust. This will lead to an overestimation of foreign investment and an underestimation of domestic investment. 10 The period starts from the beginning of 1995 and ends at the beginning of 2000. 11 The baseline scenario uses the model adjusted to take account of duty drawbacks in China.
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expected to be completed by the beginning of 2007, but the effects on foreign ownership and
income payments are expected to linger for another decade, as we will see in our results which
extend to 2020.
For comparison purposes and because the reader may find some of elements of the
simulation more convincing than others, we examine both the total effect of China’s accession,
as well as the individual contribution of five components, representing five different elements of
China’s accession agreement, to the changes in investment and welfare. These components are:
1. the gradual reduction in risk premium expected by foreign investors;
2. the removal of tariffs and quotas as outlined in the agreement;
3. the liberalization of cross-border trade in services;
4. the expected improvements in productivity in the automobile sector resulting from
accession; and
5. the liberalization of rules governing foreign commercial presence in the services
sector and associated sector-specific productivity impacts.
In light of the fact that readers may find some of these elements more convincing than
others, we examine both the total effect of China’s accession on foreign investment, as well as
the individual contribution of each of these elements of accession, to the changes in foreign
investment and welfare. In the remainder of this section, we discuss the policy scenario in detail,
including the shocks used to incorporate each of these aspects and the assumptions made.12
a) The gradual reduction in risk premium expected by foreign investors
Data on the value of foreign investment in China obtained from IMF Balance of Payment
Statistics (1999) and China’s statistical yearbook (2002: Figure 1) suggest that foreign ownership
in China has increased significantly more over the pre-accession period than was justified by the
changes in expected rates of return resulting from the pre-accession tariff cuts and the
assumption of minimizing any changes in the portfolio shares of foreign and domestic
12 Note that the liberalization of services (points 3 and 5 above) are discussed simultaneously under the heading ‘d) Services Liberalization’, due to their interrelated nature. However, in analyzing the results we chose to separate the effects of services trade liberalization and productivity improvements in the services sector for the reasons outlined above – namely that readers may be less convinced of China’s ability to attain the productivity gains assumed in this paper.
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investment in GTAP-Dyn.13 The increase in the share of foreign ownership in China may have
been the result of a number of factors including tax incentives for foreign direct investment, and
removal of restrictions on foreign direct investment in some industries (mostly notably light
manufacturing and electronics) and a decline in risk premia, which have occurred as China
gradually opened up its economy and accession to the WTO became increasingly assured.
Despite creating incentives for FDI in the nineties, as of 2002 China still has a long way
to go in terms of removing restrictions to foreign direct investment – joint ventures remain the
best way for foreigners to invest in China and certain sectors such as services were closed to
foreign investment until recently. We therefore assume that foreign ownership will continue to
increase relative to the baseline14 as risk premiums continue to fall, although the effect will
diminish gradually. Hence by 2007, any affinity by foreign investors to increase foreign
ownership in China, caused by China’s opening up to foreign investment, will most likely have
been eliminated.15
b) Tariffs and Quotas
Constructing an accurate accession scenario is a complex task – even when it comes to
tariff cuts. The tariff reductions agreed to by China as part of the accession offer were obtained
from Martin et al. (2000) and are based on China’s offer as of August, 1999. However, in many
cases, these reductions had already been implemented as part of China’s preparation for WTO
accession. The approach that we take is to compare the offer to China’s 1997 applied tariffs.
Where the binding is lower, the offer is taken as a change in policy. Table 2 shows China’s tariff
13 According to foreign investment data, the growth rate of domestic ownership in 2000 was 10% less than the model would have predicted given the actual and expected rates of return in the baseline scenario. In 2001 it was 9% less than the model predicted. 14 Some might argue that the increased share of foreign ownership should be viewed as part of the baseline scenario, reflecting the fact that it is the result of China’s broader attempts to open up its economy and introduce a rules-based system. Alternatively, it might be argued that the two are inseparable, and thus at least part of the decline in risk premiums is related to accession. We find that a good way to think of this is to consider the true “counterfactual”: What would happen if China’s accession had failed? Would this trend continue or is it more likely that foreign investors would reconsider their positions in China? We believe that the latter would have been more likely. For this reason we have chosen to include a continued rise in foreign ownership as part of China’s accession. Of course, we separate this effect for purposes of analysis and permit the reader to apply her/his own judgment in this matter. 15 This type of approach, which uses historical data to infer future changes, was formalized by Dixon and Rimmer (2002). Baldwin, Francois and Portes (1997) adopt a similar approach in modeling the impacts of EU enlargement on investment in Central and Eastern Europe.
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rates before and after accession. In the case of Taiwan (China), the cuts are based on their
announced target of 4 percent average tariffs for manufactures.16
The reduction in tariffs is assumed to occur in equal installments over the entire period
and to refer only to imported intermediate goods for the production of commodities for domestic
consumption, as well as, to other imports for final private and government consumption. China’s
tariffs on imported intermediates used for the production of exports and investment goods remain
unchanged and are zero reflecting the presence of duty exemptions. Finally, in order to avoid
biasing our accession results by permitting the government to run an increased deficit as a result
of accession, we offset these tariff cuts with increases in the current consumption tax in order to
maintain unchanging total tax revenue, relative to net national income over the period 2002 -
2007.
We also assume the quotas on China’s textiles and clothing exports to North America and
European Union will be removed by the beginning of 2007. Based on experience with
implementation of the Agreement on Textiles and Clothing under the Uruguay Round
Agreement of the WTO (Spinanger, 1999), we assume that liberalization of the quotas on
imports from China and Taiwan (China) will be back-loaded with the bulk of the impact not felt
until the final two years. Specifically, we follow the method used in Walmsley and Hertel
(2001), except that accession does not commence until 2002.
c) Productivity in the Automobiles Sector
The automobile sector is currently one of the most heavily protected industries in China,
with an average pre-accession tariff rate for vehicles of about 70%. In addition, barriers to
internal trade in automobiles have arisen in response to the efforts of individual provinces to
foster their own auto industry. Government also sets prices and limits competition in order to
favor local producers (Francois and Spinanger, 2002). As a consequence, the opening of this
sector to world trade is expected to give rise to substantial restructuring and rationalization of the
motor vehicle industry. Francois and Spinanger (2002) point out that the thirteen plants currently
producing sedans in China average only 39,000 units per year – roughly a tenth of the minimum
16 No data were available on Taiwan’s (China) offer for agriculture at the time of writing, and hence no shocks were applied. More recently data on Taiwan’s accession agreement have become available. Results using Taiwan’s actual accession agreement can be found in Ianchovichina and Walmsley (2003). The results for China, the focus of this paper, do not change significantly as a result of including Taiwan’s actual accession agreement.
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efficient scale, by world standards, and that WTO accession could bring as much as a 20%
increase in total factor productivity in the autos sector.
In this paper, we adopt the Francois and Spinanger productivity gain estimate, and just as
they do we assume that the increase in productivity of the auto’s sector is expected to occur in
the assembly of automobiles, rather than in the production of parts. Since our analysis is
dynamic, we must also distribute these gains over time. For this purpose, we assume that the
gains in productivity occur slowly, peaking in the last year of accession (2006) and then falling
back to the baseline rates by 2010 as illustrated in Figure 3.
d) Services Liberalization
As noted in the introduction, China’s commitments in the services sector “represent the
most radical services reform program negotiated in the WTO” (Mattoo, 2001, p.1) and, in this
sense, are the most significant part of China’s WTO accession package. Therefore, omitting the
services commitments from the evaluation of WTO accession,17 seriously underestimates the
gains from trade reform in China.
The WTO groups services commitments into four “modes”: (1) the delivery of services
across national borders (direct trade in services), (2) the consumption of services abroad (e.g.,
tourism), (3) commercial presence (i.e. foreign direct investment in the services sector in China),
and (4) the movement of natural persons (foreigners providing services in China in person). For
purposes of our study, we focus on modes 1 and 3, as they appear to be quantitatively the most
important, and have the strongest implications for foreign investment – particularly commitments
with respect to mode 3 - commercial presence in the services sector.
Cross-border supply of services: According to Mattoo (2001, p. 7) China has committed
to allow the cross-border supply of professional services, to remove quantitative limitations on
accountancy firms, to offer taxation services outside of ‘economically developed areas’, and
improve urban planning and legal services. Cross-border supply of education services is also
fully open. Commitments on cross border supply in the area of logistics, distribution and
transport are mixed. While nothing is offered at the wholesale distribution level, the cross-border
supply of retail services through mail-order is allowed – presumably opening the door to retail e-
17 The vast majority of studies have abstracted from commitments in services when evaluating the economy-wide impacts of China’s WTO accession.
16
commerce. In the area of transport services, there are provisions relating to cross-border supply
of airline services, as well as maritime services to the 130 ports that are open to foreign shipping
(Wenping and Findlay, 2001).
Francois and Spinanger (2002) provide estimates of the tariff equivalents of these non-
tariff barriers before and after China’s accession for wholesale and retail trade, transportation,
communication, construction, finance, insurance and real estate services, other commercial
services and other services (such as public health). We use these tariff equivalents to estimate the
reduction in price resulting from the liberalization of services. The tariff equivalents are
aggregated using weights obtained from the GTAP Data Base to determine the pre and post-
accession tariff equivalents for the three services sectors used in this analysis. (See Table 2 for
shocks for China). As with tariffs, we assume that the liberalization of direct trade in services
occurs gradually over the accession period (2002-2007). In order to introduce the impact of these
cuts in tariff equivalents on direct trade in services, we use the approach developed in Hertel,
Walmsley and Itakura (2001, henceforth HWI).
Foreign Commercial Presence in Services: From the point of view of foreign
investment, the most important aspect of the services agreement is that pertaining to commercial
presence, since this has a direct impact on the constraints facing firms interested in investing in
China’s services sector. Of special interest are the anticipated changes in telecommunications,
transport, logistics, and financial services. In the telecommunications sector, foreign companies
can provide value-added and mobile telephone services only in (and between) the three richest
metropolitan areas (Shanghai, Guanzhou and Beijing), and this must be done through joint
ventures with majority Chinese ownership. With WTO accession, by 2004, fixed line services
may also be provided by foreign companies and by the end of the accession period geographical
restrictions will be eliminated and equity restrictions will be relaxed (Mattoo, 2001). These
reforms promise to make a relatively competitive mobile phone market even more efficient,
while the fixed line service is expected to undergo major increases in productivity (Pangestu and
Mrongowius, 2001).
China’s commitments in the logistics area are particularly striking. By 2006, the
distribution services sector will be largely open to foreign investment, with few ownership
restrictions and no geographic restrictions (Mattoo, 2001). This is a sector that has hitherto been
17
largely in the domain of the state planners, with each sector organizing its own warehousing and
storage activities. At the local level, government and enterprise functions were not separated, so
the administration of the logistics sector was severely fragmented (Wenping and Findlay, 2001).
The infusion of foreign supply chain expertise could have a profound impact on productivity in
this sector. Road and rail transport services are also scheduled for full liberalization by 2007,
which opens the possibility of much more effective use of multi-modal transport activities
(Mattoo, 2001). In short, there is enormous scope for productivity gains in the key transport and
logistics activities that lubricate a modern economy.
WTO accession also has substantial implications for the financial services sector. Prior to
accession, foreign banks could only operate in a few regions, and only accept deposits from non-
residents and only in foreign currencies. Under accession, this sector will be gradually, fully
liberalized. First the geographic restrictions will be eliminated, then the local currency restriction
will be dropped in selected regions and by 2006, the banking services will be fully liberalized.
Similar liberalization will be undertaken in the insurance services sector. These changes promise
to greatly increase competition and productivity in financial services.
Since most of the reforms to rules governing foreign establishment of commercial
presence in services are phased in gradually, we implement the asymmetric, triangular pattern of
productivity shocks (Figure 3). The maximum deviation from baseline occurs in 2007, when
productivity growth is assumed to be 1%/year relative to the baseline rate of growth.18 This
WTO-induced effect subsequently diminishes and disappears by 2010, leaving total factor
productivity in the services sector 4.58% higher than under the baseline in 2010.
This productivity enhancement appears to be rather modest in light of the major reforms
being undertaken by China and the findings of Mai, Horridge and Perkins (2003), which uses
historical simulations to estimate potential productivity growth in services in China over the
accession period. They predict a productivity growth of 2.7% per year in services over a 10 year
period following accession. We therefore also explore the effect of a higher rate of productivity
growth – where productivity growth is assumed to peak at 2.7%/year relative to the baseline rate
18 Note there is no sector-specific productivity differential in the baseline. Region-specific productivity is calibrated to achieve forecasted GDP growth.
18
of growth (See Appendix 1).19 As we will see below, even these smaller cumulative productivity
shocks are sufficient to play a dominant role in the overall accession story.
4. Impact of China’s WTO Accession
In this section, the results of China’s accession are discussed. We begin by providing an
overview of the macro-economic effects of accession on capital accumulation and investment –
before turning to the specific question at hand – namely the impact on domestic and foreign
ownership. The section concludes with a summary of the long run welfare consequences of
China’s accession.
Macroeconomic impact on Capital Accumulation
A comprehensive picture of the global impact of China’s accession is given in Table 3.
The results report the cumulative percentage changes relative to the baseline at the beginning of
2020, thus highlighting the long-run effects of China’s entry into the WTO. Overall the results
concur with the findings of other research - China and Taiwan (China) are the primary
beneficiaries from China’s accession in terms of both production and welfare (Table 3). In the
long run, with the additional accumulation of capital, these benefits are even more pronounced.
Here, we trace through the major mechanisms determining the changes in investment, capital and
real GDP.
As a result of China’s accession the rental price of capital is 4.3 percent higher than the
baseline by 2007. The increase in capital’s rental price is the result of increased demand for
capital by all industries, but in particular the wearing apparel and auto sectors, where exports
increase as a result of the removal of tariffs and quotas (and productivity gains in the case of
autos), and the services sectors, where production has increased as a result of the services
liberalization and productivity gains. The effect of liberalization in cross border trade in services
on the rental price of capital is small (0.1 percent increase in real GDP)20 when compared to the
potential impact of productivity growth in services, which accounts for 12.2 percent of the 22.5
percent increase in real GDP.
19 This leads to a cumulative change in services productivity of 12.794, substantially less than the total factor productivity estimated by Mai et al. (2003) which estimated productivity growth of 2.7% per year. However, Mai et al.’s estimates may be overestimates since they abstract from reform at the border in their study. 20 This is because cross-border trade in services is a relatively small share of total trade.
19
In addition, the price of capital goods in China gradually declines over the accession
period.21 The decline in the price of capital goods is primarily fueled by declines in the prices of
domestic intermediates, purchased by the capital goods sector. These prices fall as a result of the
removal of tariffs on their imported intermediates and as a result of the productivity gains in the
automobile and service sectors. Again, the liberalization of cross border trade in services plays a
minor role in the decline in the price of capital goods.
The combined effect of the rise in the rental price of capital and the decline in the price of
capital goods causes the rate of return on investment in China to increase.22 Figure 4 illustrates
the effect of the various features of China’s accession on the rate of return. The removal of tariffs
and the productivity shocks appear to have the largest impact on the rates of return in China,
while the effect of liberalization of cross border trade in services is minimal, due to its limited
effect on the price of capital goods and the rental price.
Investment and hence capital stocks increase in response to the higher rates of return in
China as a result of WTO accession. These larger capital stocks serve to gradually bring the rate
of return down and closer to the global rate of return after 2007 when accession is complete.
Eventually, the rate of return in China falls below that in the baseline scenario. This is the result
of the capital accumulation mechanisms in the model, which allocate investment in such a way
as to eliminate differences in the rates of return across regions.
As a result of WTO accession, 2020 capital stocks increase by 25.8 percent and real GDP
by 22.5 percent, relative to the baseline (Table 3). Figure 5 divides the effect on real GDP
according to the five components of China’s accession. Those components, which lead to
increases in the rates of return on capital, have the greatest impact on real GDP.
As mentioned previously, it was assumed that any tax revenue lost as a result of lower
tariffs would be replaced with consumption taxes. The power of these taxes rises by 1.32 percent
in 2007. As the productivity gains in autos and services take hold, this revenue replacement
requirement disappears.
21 This decline would have been much larger if we had not incorporated the pre-existing duty drawbacks on imported intermediate imports purchased for the production of capital goods. 22 The rate of return is the ratio of these two prices. It ignores capital gains (losses) as GTAP-Dyn is a recursive dynamic model (Ianchovichina and McDougall, 2001).
20
Domestic and Foreign Ownership
In this paper we are particularly interested in the impact of WTO accession on domestic
and foreign ownership of those capital stocks. Figure 6 shows that the share of foreign ownership
in China grew strongly between 1995 and 2002. After 2002, however, growth in foreign
ownership in the baseline occurs at a more modest rate (Figure 7). As a consequence, the share
of foreign investment in the baseline falls between 2002 and 2020. This decline in the share is
due to the fact that China’s income and hence savings are growing faster than other regions,
hence Chinese households can fund more of China’s investment.
With rates of return increasing as a result of China’s accession, foreign investment is
attracted to China (Figure 7), the share of foreign ownership in Chinese assets also rises (Figure
6) as China’s regional investment rises faster than saving. Table 3 reports that foreign wealth
located in Chinese assets increases by approximately 126 percent, relative to the baseline by
2020. Most of this increase is due to the boost that China’s accession to the WTO is expected to
give to productivity (associated with the rise in foreign commercial presence in the service
sectors), followed by the reduction in risk premiums,23 and tariff liberalization (Figure 7).
Foreign (and domestic) ownership are little affected by the liberalization of cross border trade in
services.
Each of the elements of WTO accession raises the share of foreign ownership relative to
the baseline (Figure 6), however it is only when restrictions on the foreign commercial presence
in services are eliminated that the share rises in absolute terms. Eventually however, income and
hence saving in China rise sufficiently to cause the domestic share of this investment to rise and
the foreign share to fall (2010).
China’s accession also increases the total wealth of Chinese households. Figure 8 shows
the share of this wealth allocated to foreign assets. In the baseline Chinese households increase
their holdings of foreign assets. However with China’s accession, higher relative rates of return
at home make domestic investments more attractive and the share of Chinese wealth located in
foreign assets falls, as the share in domestic firms rises.
23 In Figure 7 the line labeled ‘risk’ shows the effect on foreign ownership if we assume that the current rising trend in foreign ownership continues. In this case the marked slowdown in growth of foreign ownership in the baseline is reduced. The decline in the share of foreign ownership still occurs, although the effect is delayed (Figure 6).
21
The increase in capital flows into China is mirrored in the country’s trade balance relative
GDP -- as reported in Figure 9. The increase in capital flows24 causes the trade balance to
initially decline. By 2020 when foreign capital flows level off, the increase in income payments
to foreign owners of capital causes the trade balance to improve. In the other regions, by 2020,
the trade balance declines as imports rise faster than exports in the developed economies, or in
the case of the developing economies, as exports decline (Table 3).
It is important to reiterate that domestic and foreign shares of China’s investment are held
constant, subject to adding up constraints, and hence are only affected by the relative ability of
domestic and foreign households to fund investment (i.e. their savings). The model does not take
into account other factors which may influence the decisions of foreign and domestic investors,
such as differences in their expectations, delays in reforms to China’s inefficient state enterprises
or financial markets and many of the other problems outlined in the Economist (2000) which
may continue to cause foreign investors to be cautious, even after accession. Moreover capital
flows relate to investment in physical goods, not the movement of financial capital.
Consequently the model does not take account of the possibility that as China opens up its
financial markets there will be an outflow of financial capital as Chinese investors seek to
diversify their own portfolios. This would increase the extent to which foreign investors could
fund new investments in China.
All countries, other than China and Taiwan (China), increase their long run foreign
ownership, which is invested primarily in China and to a lesser extent Taiwan (China) (Table 3).
By 2020 China reduces its foreign investments abroad, relative to the baseline, choosing instead
to invest domestically (Table 3). In contrast to China, real GDP, investment and wealth in the
South East and South Asian economies are adversely affected by China’s accession to the WTO.
This is primarily due to increased competition in the wearing apparel and textiles markets as
China’s quotas are removed. Total household wealth in South East Asia, however, rises due to
the large increase in foreign investment. The Newly Industrialized Economies (NIEs), on the
other hand, supply the growing Chinese sectors with intermediate inputs, hence real GDP, capital
24 Financial capital flows, which also affect the capital account, and hence the trade balance, are not included in this model. All foreign capital flows relate to foreign investment in physical capital.
22
and foreign ownership in the NIEs fall only marginally. The other developed and developing
countries also increase their ownership of foreign assets.
Note that if productivity in the services sectors were to increase to a maximum of 2.7%
by 2007 (a cumulative increase in productivity of 12% over the baseline), as compared to 1% in
the simulation outlined above, foreign investment in China would more than triple as a result of
China’s accession. Real GDP in China would increase by 35.7% as compared to the current
increase of 22.5%.25
Welfare
Since GTAP-Dyn does not incorporate an inter-temporal utility function, determining the
effect of China’s accession on welfare is a difficult task as there is no obvious way of
aggregating welfare over time. In addition, the static welfare decomposition that we rely on for
purposes of analysis (Huff and Hertel, 2001) is path dependent.26 For these reasons, we have
opted for a relatively simple, straightforward approach to welfare analysis in which a single
comparative static simulation27 is performed in the year 2020 to determine the difference in static
welfare – at that point in time -- with and without China’s accession.
The final column of Table 3 reports the percentage change in the representative regional
household’s static utility in 2020 owing to China’s WTO accession. This change is largest for
China (16%), followed by Taiwan (China) with a 3.1% increase in 2020 welfare. Other changes
are less than 1%. With the exception of South and South East Asia, all regions gain from China’s
WTO accession.
The first column in Table 4 reports the Equivalent Variation (EV) associated with the
changes in regional household utility, and the remainder of that table uses the Huff/Hertel
decomposition technique to explain the sources of welfare changes in each region. In the case of
China, we see that US$57 billion of the gain in 2020 is due to improved allocative efficiency –
lower tariffs improve the allocation of resources between domestic production and imports. The
second column of Table 4 shows that China’s terms of trade deteriorate as she exports more in
25 The macro results in 2020 for this alternative experiment are provided in Appendix 2. 26 This means that the welfare results are dependent on the shares in the data base. In a dynamic model the data base is updated each period, and therefore the shares will depend on the policy shock, and hence the path taken. 27 Further details about the comparative static simulation are provided in Appendix 2.
23
order to pay for her increased imports. Also, the abolition of the MFA quotas on textiles and
apparel means that the associated exporter rents get dissipated in lower export prices. Because
WTO accession stimulates investment in China, the capital stock is higher and this contributes
US$40.4 billion to welfare (Table 4). However, a substantial portion of this new investment is
foreign-owned and so the associated income payments go overseas. This flow translates into an
offsetting US$13 billion deduction from China’s welfare in the foreign ownership column of
Table 4. The other major contributor to welfare in 2020 is the improved productivity. This
accounts for a US$31 billion increment to static, 2020 welfare.
The OECD countries tend to experience a decline in allocative efficiency (Table 4). This
is a result of the change in production of taxed or subsidized sectors, including: automobiles
(Japan), trade and transport (USA) and/or agriculture (EU28) sectors resulting from the
production changes in China. The impact in other regions is mixed. Most striking is the US$2
billion decline in 2020 static efficiency in South Asia, where the volume of trade falls under
China’s accession. Apart from China and South Asia, the terms of trade improve for all other
regions.29 The capital and foreign ownership columns are largely offsetting in the non-China
regions, since the lower domestic capital stock is offset by increased earnings on foreign
investments.
Thus far, we have discussed the economic mechanisms behind the welfare impacts. But
which elements of the accession package contribute most to these welfare gains? In Table 5, the
welfare (EV) results are decomposed according to the impact on welfare of each element of the
accession package.30 Overall, the changes in China’s welfare are primarily (85%) due to the
productivity improvements in the automobiles and services sectors. The reduction in tariffs by
China and the expansion of US and EU quotas on textiles and wearing apparel account for 13
percent of the total welfare gains or $US13.8 billion.31 Hence 52% of the gains to China are from
28 The fall in allocative efficiency in the EU, resulting from productivity gains in China’s automobile sector, is driven by an increase in agricultural production, which is heavily subsidized. Production of automobiles falls, as expected, however the rise in imports of automobiles, which are subject to high tariff rates, causes welfare to rise. 29 The increase is particularly strong for North America and Europe, where the demand for exports rises and the elimination of textile and apparel quotas on imports results in lower prices for those products. 30 A complete decomposition of the welfare changes resulting from each of the five elements of accession is provided in Appendix 2. 31 This finding is consistent with other studies that take into account the duty drawbacks currently in place in China (Ianchovichina et al., 2001).
24
the productivity gains in services, an effect which is missed by most of the studies on China
accession in the literature.32
On the other hand, 52% of the gains to the developed countries are the result of the
elimination of tariffs and quotas, as compared to only 13% for China. However, the
improvements in productivity in China still account for a substantial proportion (almost 40%) of
the welfare gains of the other regions. Hence for both China and the other regions these
productivity gains are an important aspect of China’s accession agreement.
6. Conclusion
Foreign investment was a focal point in China’s negotiations for accession to the WTO.
China has aggressively pursued foreign investment over the past decade – albeit with significant
limitations on foreign entry in certain sectors – particularly services. Accordingly, increasing
access for foreign investors in the services sectors has been of paramount importance to the US
and European negotiators in their dealings with China. In addition, WTO accession will lead to a
reduction in tariffs, elimination of quotas on exports of textiles and apparel, and reduction in the
barriers to cross-border supply of services. This paper focuses on these elements of China’s
WTO accession, comparing two alternative time paths of investment and ownership in the
Chinese economy over the coming two decades: a no-accession baseline (counterfactual)
scenario, and projections under WTO accession.
We used a modified version of the dynamic global applied general equilibrium model,
GTAP-Dyn, which explicitly models capital accumulation and foreign ownership as well as
taking account of China’s existing duty exemption system. Our results show that China’s
accession to the WTO would boost the Chinese economy and raise rates of return. The resulting
increase in capital stocks would be financed by increased domestic investment and foreign
investment from industrialized and newly industrialize economies in East Asia, North America
and Europe.
32 China’s accession may also result in productivity gains in other manufacturing sectors. In textiles and footwear, Claro (2001) states that the adoption rates for foreign technology are between 30 and 62% for collective enterprises. Mai et al. (2003) also estimate significant productivity gains in the manufacturing sector. These are not captured here.
25
Central to the increase in China’s capital stock are the anticipated productivity gains in
the automobile and service sectors. In the automobile sector, this improvement is expected to be
fueled by a rationalization of production, as the number of production facilities falls, but the
length of run for any given facility increases (Francois and Spinanger, 2002). In the case of
services, the productivity gains are expected to come from the opening of the Chinese market to
foreign investment. In particular, telecommunications, banking, insurance, logistics and
transportation are expected to experience substantial productivity gains as foreign investors
induce changes in the organization and operation of these activities. Rather than model the
elimination of these barriers to commercial presence directly, we adopt a “dual” approach,
whereby we postulate an associated gain in productivity as part of our accession scenario,
thereby observing how much foreign investment such gains are likely to sustain. While this part
of our analysis is clearly speculative, these productivity shocks are well within the plausible
range identified by Mai et al (2003). Since the services component of the accession package is a
critical factor in determining the overall impact on GDP and welfare – both in China and in her
trade and investment partner economies, further research on the likely productivity gains
following accession needs to be undertaken.
The overall size of the potential gains to China is quite substantial. We estimate that GDP
could be nearly 22.5% higher in 2020 as a result of WTO accession. The static welfare gains are
lower (16% in 2020) due to the fact that a substantial share of the additional investment comes
from overseas. Nevertheless, these impacts are quite large, and far larger than those predicted by
earlier studies which have ignored the impact of accession on productivity in the services sector
of China, as well abstracting from capital accumulation and foreign investment. Future research
should be directed towards narrowing the uncertainty associated with the impact of accession on
productivity in services.
26
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Figure 1: Foreign Investment in China
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50000
60000
1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
US$
Mill
ions
Sources: IMF Balance of Payments Statistics, 1999 and China’s statistical yearbook, BNP Paribus Peregrine (US$ millions).
Figure 2: Expected and Actual Rate of Return Schedules
Source: Ianchovichina and McDougall (2001)
1
2
RT
RA
RE
Actual ROR Schedule
Expected ROR Schedule
Rate of Return
Capital K
29
Figure 3: Automobile and Service Sector Productivitya shocks (% point differences from baseline growth rates)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
% c
hang
e in
Pro
duct
ivity
Autos Productivity
Services Productivity
Alternative ServicesProductivity
a. ‘Alternative services productivity’ refers to the case where service sector productivity peaks at 2.7% (this correspond to the annual productivity gain estimated by Mai et al., 2003). The results of this scenario are examined in Appendix 1.
Figure 4: Cumulative Percentage Differences from Baseline in China’s Actual Rate of Returna
-3
-2
-1
0
1
2
3
4
5
6
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Cum
% D
iffe
renc
es r
elat
ive
to B
asel
ine
Risk Premium
Tariffs
Cross Border Services Liberalisation
Autos productivity
Services Productivity
a. Each curve shows the cumulative % difference between the baseline and the policy. The policy is assumed to be the particular aspect referred to plus all previous shocks listed. Source: Authors’ simulations with GTAP-Dyn.
30
Figure 5: Cumulative Percentage Differences from Baseline in China’s Real GDPa
0
5
10
15
20
25
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Cum
% D
iffe
renc
es r
elat
ive
to B
asel
ine
Risk Premium Tariffs
Cross Border Services Liberalisation Autos productivity
Services Productivity
a. Each curve shows the cumulative % difference between the baseline and the policy. The policy is assumed to be the particular aspect referred to plus all previous shocks. Source: Authors’ simulations with GTAP-Dyn.
Figure 6: Share of Foreign Ownership of Chinese Assetsa
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
%
Baseline Risk premium
Tariffs Cross Border Services liberalisation
Autos Productivity Services Productivity
a. Each curve shows the share of foreign ownership of Chinese assets over time resulting from the particular aspect referred to plus all previous shocks. Source: Authors’ simulations with GTAP-Dyn.
31
Figure 7: Gross Foreign Ownership of Chinese Assetsa
0
50
100
150
200
250
300
350
400
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Cum
ulat
ive %
Cha
nges
Baseline
Risk Premium
Tariffs
Cross Border Services Liberalisation
Autos Productivity
Services Productivity
a. Each curve shows the cumulative % change of foreign ownership of Chinese assets, in the baseline and under each of the policy experiments undertaken. Source: Authors’ simulations with GTAP-Dyn.
Figure 8: Share of Chinese Wealth located in Foreign Assetsa
0
5
10
15
20
25
30
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
%
Baseline Risk premium
Tariffs Cross Border Services liberalisation
Autos Productivity Services Productivity
a. Each curve shows the share of Chinese assets located abroad over time resulting from the particular aspect referred to plus all previous shocks.
32
Figure 9: Cumulative Difference from Baseline of the Change in China’s Trade Balance relative to GDP
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Cum
% D
iffe
renc
es relat
ive to
Bas
elin
e
Risk Premium Tariffs
Cross Border Services Liberalisation Autos productivity
Services productivity
a. Each curve shows the change in the trade balance relative to GDP between the baseline and the policy. The policy is assumed to be the particular aspect referred to plus all previous shocks. Source: Authors’ simulations with GTAP-Dyn.
Table 1: List of Countries and Commodities of the Study
Regions Sectors/Commodities
China Crops
Taiwan (China) Livestock
North America Processed food and Beverages and Tobacco
Western Europe Mining, fish, forestry, petroleum,
Japan Textiles Newly Industrializing
Countries Wearing apparel
South East Asia Metals and Chemicals
South Asia Automobiles and parts
Latin America Electronics
Africa and Middle East Other Manufactures
Rest of World Household Utilities
Trade and Transport
Other Services
33
Table 2: Tariff Barriers, Services Liberalization and Productivity Gains for Chinaa
Sectors 1995 tariffsb Tariffs prior
to Accessionc
Tariffs post Accessiond
Cross-border Services
Liberalizatione Productivityf
Crops 3.92 -0.39 -0.39
Livestock 7.33 2.30 2.30
Food and Beverages 21.51 20.90 20.25
Extraction 8.50 5.45 3.46
Textiles 57.52 30.39 9.25
Wearing apparel 76.12 31.84 15.80 Metals and
Chemical products 19.26 14.82 10.87
Autos 129.23 31.34 20.37 20
Electronics 22.16 12.75 4.93
Other manufactures 23.48 17.37 11.06
Household utilities 0.12 0.16 0.15 5.90
(1.15% p.a.) 4.6
Trade and transport 0.00 0.00 0.00 0.92
(0.18% p.a.) 4.6
Other services 4.20 4.20 4.20 10.48
(2.01% p.a.) 4.6
a. Table does not include details of shocks to incorporate the change in the risk premium or the removal of MFA quotas. b. Tariff Rates in GTAP v.4 data base (1995). c. Tariff Rates after reductions in baseline. This is due to the fact that China has already undertaken considerable trade liberalization prior to its accession d. Tariff rates after accession, as per WTO accession agreement (as of August 1999). e. Cumulative Shocks. Yearly shocks in brackets. f. Cumulative Shocks. Shocks are applied as per Figure 3.
34
Tab
le 3
: Im
pact
of
Chi
na’s
Acc
essi
on (
2020
)a
R
eal
GD
P
Cap
ital
St
ocks
Cha
nge
in
Tra
de
Bal
ance
: re
port
as
% o
f G
DP
Act
ual
Rat
e of
R
etur
n
Reg
iona
l W
ealt
h in
D
omes
tic
Ass
ets
Reg
iona
l W
ealt
h in
F
orei
gn
Ass
ets
For
eign
W
ealt
h lo
cate
d in
re
gion
Wea
lth
of
Hou
seho
ld
Wel
fare
(p.c
. in
utili
ty)
Chi
na
22.5
2 25
.82
11.2
2 -2
.37
21.0
5 -1
9.66
12
6.54
9.
00
15.9
9 T
aiw
an (
Chi
na)
4.06
9.
94
2.09
-0
.86
9.72
-5
.05
26.7
9 3.
16
3.06
N
orth
Am
eric
a -0
.23
-0.6
5 -0
.31
0.36
0.
15
3.45
-3
.04
0.41
0.
08
Wes
tern
Eur
ope
-0.2
7 -0
.87
-0.3
9 0.
57
0.35
1.
47
-0.7
5 0.
73
0.00
Ja
pan
-0.4
6 -0
.92
-0.4
3 0.
46
0.08
2.
83
-2.5
9 0.
83
0.02
O
ther
NIC
s -0
.10
-0.0
7 -0
.12
0.29
0.
83
2.26
-0
.58
1.01
0.
28
Sout
h E
ast A
sia
-1.0
8 -1
.92
0.05
0.
30
-1.2
2 5.
42
-7.4
4 0.
56
-0.2
1 So
uth
Asi
a -0
.86
-1.0
9 -0
.55
0.42
-0
.76
4.93
-6
.15
-0.7
5 -0
.66
Lat
in A
mer
ica
-0.3
1 -0
.65
-0.2
3 0.
25
0.78
2.
98
-1.3
7 0.
79
0.10
A
fric
a an
d M
iddl
e E
ast
-0.4
3 -0
.85
-0.2
7 0.
44
0.50
2.
53
-1.4
9 0.
55
0.05
R
OW
0.
05
-0.2
8 -0
.34
0.41
0.
81
1.71
-0
.09
0.82
0.
48
a. U
nles
s ot
herw
ise
stat
es r
esul
ts r
epre
sent
cum
ulat
ive
% c
hang
es f
rom
bas
elin
e fr
om a
ll fi
ve c
ompo
nent
s of
Chi
na’s
Acc
essi
on.
Sour
ce: A
utho
rs’
sim
ulat
ions
wit
h G
TA
P-D
yn.
35
Table 4: Decomposition of Welfare (2020, $US million)
Total Welfare
Allocative Efficiency
Terms of Trade Capital Foreign
Ownership Tech
changea Otherb
China 103,433 57,625 -9,687 40,408 -13,255 30,559 -2,218 Taiwan (China) 7,763 1,275 2,457 5,912 -1,886 609 -604 North America 5,802 -454 8,787 -12,794 10,404 0 -141
Western Europe -122 -3,970 2,971 -9,829 9,432 0 1,275 Japan 1,074 -5,117 836 -9,464 16,743 0 -1,925
Other NICs 1,527 -204 1,318 -135 567 0 -18 South East
Asia -1,032 -88 574 -3,729 2,349 0 -139 South Asia -2,570 -2,110 -554 -908 758 0 243
Latin America 1,169 281 1,780 -3,554 1,860 0 802 Africa and
Middle East 528 -730 1,888 -2,387 1,045 0 712 ROW 6,078 2,807 4,218 -1,072 -868 0 992 Total 123,649 49,315 14,588 2,449 27,150 31,168 -1,022
a. Due to the productivity shocks in the automobile and services sectors. b. Other includes changes in welfare due to changes in the price of saving relative to the price of capital goods and due to changes in marginal utility. Source: Authors’ simulations with GTAP-Dyn.
Table 5: Welfare Decomposition by Element of WTO Accession (2020 $US millions)
Total Risk
premiums
Tariffs and Quotas
Services Trade liberalization
Autos Productivity
Services Productivity
China 103,433 -132 13,848 522 34,746 54,448 Taiwan (China) 7,763 7 6,418 521 141 675 North America 5,802 18 5,395 246 -2,002 2,144 Western Europe -122 137 2,464 199 -2,518 -405 Japan 1,074 135 1,863 66 -2,376 1,386 Other NICs 1,527 3 797 89 317 321 South East Asia -1,032 7 -2,320 2 2,001 -722 South Asia -2,570 0 -1,504 0 -816 -250 Latin America 1,169 -3 -188 51 625 685 Africa and Middle East 528 -4 -217 67 888 -207 ROW 6,078 -4 210 53 3,922 1,897 Total 123,649 164 26,767 1,817 34,928 59,972
Source: Authors’ simulations with GTAP-Dyn.
36
RE
VIE
WE
R A
PP
EN
DIC
ES
App
endi
x 1:
Ser
vice
s P
rodu
ctiv
ity
Tab
le A
1.1
belo
w s
how
s th
e re
sults
of
Chi
na’s
acc
essi
on, a
ssum
ing
a cu
mul
ativ
e sh
ock
of 8
.3%
to p
rodu
ctiv
ity in
the
serv
ices
sec
tors
.
Tab
le A
1.1:
Im
pact
of
Chi
na’s
Acc
essi
on (
2020
)a
R
eal
GD
Pb
Cap
ital
St
ocks
Cha
nge
in
Tra
de
Bal
ance
: re
port
as
% o
f G
DP
Act
ual
Rat
e of
R
etur
n
Reg
iona
l W
ealt
h in
D
omes
tic
Ass
ets
Reg
iona
l W
ealt
h in
F
orei
gn
Ass
ets
For
eign
W
ealt
h lo
cate
d in
re
gion
Wea
lth
of
Hou
seho
ld
Wel
fare
b
(p.c
. in
utili
ty)
Chi
na
45.5
9 55
.45
21.5
6 -4
.51
40.6
9 -4
3.77
33
7.21
15
.69
24.7
2 T
aiw
an (
Chi
na)
4.25
10
.52
2.07
-0
.63
11.5
9 -3
.77
29.4
1 4.
77
3.35
N
orth
Am
eric
a -0
.47
-1.3
0 -0
.46
0.77
0.
90
7.69
-5
.47
1.44
0.
12
Wes
tern
Eur
ope
-0.6
1 -1
.89
-1.5
0 1.
24
1.01
3.
51
-1.4
4 1.
86
-0.0
1 Ja
pan
-0.9
6 -1
.95
-5.1
2 1.
01
0.33
6.
39
-5.3
8 1.
97
0.06
O
ther
NIC
s -0
.63
-1.1
9 -0
.11
0.67
1.
24
8.89
-5
.87
2.22
0.
35
Sout
h E
ast A
sia
-2.1
1 -3
.56
0.43
0.
49
-1.6
7 10
.98
-12.
88
1.73
-0
.38
Sout
h A
sia
-1.2
9 -1
.87
-0.6
1 0.
80
0.21
12
.37
-10.
64
0.24
-0
.73
Lat
in A
mer
ica
-0.6
7 -1
.39
-0.3
7 0.
54
2.09
6.
95
-2.5
5 2.
11
0.17
A
fric
a an
d M
iddl
e E
ast
-0.9
8 -1
.89
-0.5
1 0.
99
1.58
6.
14
-2.7
9 1.
69
0.03
R
OW
-0
.22
-1.0
8 -0
.61
0.93
2.
22
5.16
-0
.63
2.27
0.
65
a. U
nles
s ot
herw
ise
stat
ed r
esul
ts r
epre
sent
% c
hang
es f
rom
bas
elin
e fr
om a
ll f
ive
com
pone
nts
of C
hina
’s A
cces
sion
.
Sour
ce: A
utho
rs’
sim
ulat
ions
with
GT
AP-
Dyn
.
37
Appendix 2: The Welfare Decomposition
The comparative static simulation is designed in such a way as to find the difference between
the baseline and the policy results in 2020 (i.e. the difference between the base and policy lines is
shown in Figure A2.1 as the distance AB). The idea of the comparative static simulation is to start
with a common initial data base – the updated baseline data in 2020 – and apply various shocks to the
data to obtain the updated policy data base (i.e. move from A to B in Figure A2.1).
The shocks applied to obtain the updated data include the original cumulative policy shocks
to risk premium, tariffs and quotas, services liberalization and productivity implemented as part of
China’s accession to the WTO; shocks to capital stocks and wealth to incorporate the accumulation
effects from the GTAP-Dyn into the comparative static simulation and finally to the general price
level. These accumulation affects are very important if we wish to include the dynamic effects of
China’s accession.
All variables, which change endogenously as time passes by (i.e. depend on time in the
model), are shocked. These include capital, the normal rate of growth of capital, the expected rate of
return, wealth of households and wealth located in the firm. Finally, an adjustment may be required in
the general price level to accommodate path dependency in the numeraire. This is due to the fact that
in GTAP-Dyn the numeraire is a composite price, which again depends on shares and the path
taken.33 To remove any path dependency we need to either, change the numeraire to a basic price and
shock it by the cumulative percentage change found in GTAP-Dyn simulations or estimate the effect
of path dependency on the numeraire and shock the numeraire by this amount. Both of these methods
should provide the same result.
The decomposed welfare results for each of the five aspects of China’s accession are
provided in Table A2.1, Part I to V, below.
33 The standard numeraire in the GTAP-Dyn model is used (psavewld). This is a weighted average of the price of saving in all regions.
38
Figure A2.1: The Welfare Decomposition
Table A2.1: Decomposition of Welfare by the Five elements of China’s Accession (2020, $US Millions)
Part I: Risk
Total Welfare
Allocative Efficiency
Terms of Trade Capital Foreign
Ownership Tech
change Othera
China -131.82 1.27 -6.81 2.20 -132.33 0.00 3.85 Taiwan (China) 7.36 0.12 0.36 -0.36 7.74 0.00 -0.49 North America 18.04 0.57 1.88 -27.70 43.78 0.00 -0.50 Western Europe 136.96 17.75 7.31 -23.24 145.08 0.00 -9.94
Japan 134.51 -0.18 8.88 -17.81 148.40 0.00 -4.77 Other NICs 3.06 -0.90 0.50 -4.93 8.70 0.00 -0.30
South East Asia 7.20 -0.67 0.49 -2.97 10.72 0.00 -0.36 South Asia -0.39 -0.37 0.23 -0.98 0.73 0.00 0.00
Latin America -3.37 -1.03 0.01 -9.34 6.79 0.00 0.19 Africa and
Middle East -3.60 -2.62 0.71 -6.68 4.82 0.00 0.18 ROW -3.66 -0.61 -0.58 -8.63 5.98 0.00 0.19 Total 164.31 13.33 12.97 -100.45 250.41 0.00 -11.95
Policy
Baseline A
B
Time
Value
2020
39
Part II: Tariffs and Quotas
Total Welfare
Allocative Efficiency
Terms of Trade Capital Foreign
Ownership Tech
change Othera
China 13,848.02 12,098.36 -4,032.78 9,459.50 -3,509.84 0.00 -167.22 Taiwan (China) 6,418.21 1,549.30 1,793.53 5,412.28 -1,953.83 0.00 -383.08 North America 5,395.40 1,581.45 4,955.88 -4,496.26 3,474.43 0.00 -120.11 Western Europe 2,463.80 657.74 1,950.76 -2,420.80 2,218.03 0.00 58.07
Japan 1,863.35 -466.69 804.90 -2,232.41 4,375.17 0.00 -617.60 Other NICs 796.83 147.35 516.19 226.57 -61.76 0.00 -31.52
South East Asia -2,320.27 -518.35 -306.57 -2,698.58 1,176.89 0.00 26.35 South Asia -1,503.75 -828.38 -492.26 -1,088.85 808.21 0.00 97.53
Latin America -188.47 -108.51 231.95 -1,517.70 1,014.25 0.00 191.55 Africa and
Middle East -216.52 -272.60 303.69 -833.97 373.02 0.00 213.34 ROW 210.40 86.06 453.22 -909.16 214.63 0.00 365.65 Total 26,766.99 13,925.71 6,178.52 -1,099.38 8,129.20 0.00 -367.05
Part III: Services Liberalization
Total Welfare
Allocative Efficiency
Terms of Trade Capital Foreign
Ownership Tech
change Othera
China 522.38 119.75 -119.00 45.01 35.00 447.71 -6.09 Taiwan (China) 521.49 44.22 -142.31 124.99 -75.85 605.30 -34.86 North America 246.34 71.51 175.71 -66.65 71.13 0.00 -5.35 Western Europe 199.27 56.42 135.98 32.00 -20.18 0.00 -4.96
Japan 65.66 -24.91 38.03 -81.22 158.21 0.00 -24.45 Other NICs 89.37 -4.32 72.61 60.33 -33.07 0.00 -6.18
South East Asia 1.53 -12.25 17.62 -18.08 17.06 0.00 -2.82 South Asia 0.34 -11.79 11.10 12.97 -12.33 0.00 0.40
Latin America 51.50 18.58 45.40 13.69 -45.67 0.00 19.50 Africa and
Middle East 66.71 26.81 42.40 4.66 -25.07 0.00 17.91 ROW 52.78 17.44 44.93 -12.20 -15.15 0.00 17.77 Total 1,817.38 301.47 322.47 115.49 54.08 1,053.01 -29.14
40
Part IV: Autos Productivity
Total Welfare
Allocative Efficiency
Terms of Trade Capital Foreign
Ownership Tech
change Othera
China 34,746.38 26,505.38 -1,067.23 7,175.47 -709.77 4,119.91 -1,277.38 Taiwan (China) 140.97 -344.36 379.54 168.60 -73.81 1.72 9.29 North America -2,002.05 -1,634.38 -540.24 -1,453.90 1,733.69 0.00 -107.22 Western Europe -2,517.51 -1,512.21 -1,133.35 -1,482.17 1,196.41 0.00 413.81
Japan -2,375.91 -2,184.18 -490.79 -1,370.44 1,394.52 0.00 274.99 Other NICs 316.88 -264.40 327.96 702.95 -458.47 0.00 8.84
South East Asia 2,001.15 833.30 609.95 635.55 -43.97 0.00 -33.67 South Asia -816.25 -939.99 -129.82 488.11 -309.89 0.00 75.34
Latin America 624.57 229.57 326.06 5.84 141.32 0.00 -78.22 Africa and
Middle East 888.22 88.06 819.66 -70.16 338.40 0.00 -287.73 ROW 3,921.58 2,198.78 1,693.60 1,474.33 -956.31 0.00 -488.82 Total 34,928.03 22,975.57 795.34 6,274.18 2,252.10 4,121.63 -1,490.79
Part V: Services Productivity
Total Welfare
Allocative Efficiency
Terms of Trade Capital Foreign
Ownership Tech
change Othera
China 54,447.96 18,900.66 -4,460.70 23,726.21 -8,937.76 25,991.08 -771.52 Taiwan (China) 675.07 26.12 426.01 206.38 209.49 2.17 -195.11 North America 2,143.78 -473.57 4,193.41 -6,749.43 5,080.82 0.00 92.56 Western Europe -404.82 -3,190.17 2,010.23 -5,935.12 5,892.66 0.00 817.59
Japan 1,385.92 -2,440.99 475.13 -5,761.98 10,666.72 0.00 -1,552.96 Other NICs 321.16 -82.22 400.61 -1,120.11 1,111.89 0.00 10.99
South East Asia -721.72 -389.63 252.78 -1,644.62 1,188.64 0.00 -128.89 South Asia -250.20 -329.54 56.95 -318.82 271.31 0.00 69.89
Latin America 684.91 142.54 1,176.55 -2,046.39 743.08 0.00 669.13 Africa and
Middle East -206.76 -569.21 721.32 -1,480.97 354.11 0.00 767.98 ROW 1,896.52 505.12 2,026.68 -1,616.03 -116.70 0.00 1,097.45 Total 59,971.83 12,099.12 7,278.97 -2,740.90 16,464.27 25,993.25 877.12
a. Other includes changes in welfare due to changes in the price of saving relative to the price of capital goods and to changes in marginal utility.